Reliability assessment of a wind integrated hydro-thermal power system
Bibliographic record
Abstract
Wind energy has received widespread public support, and as a result, wind power penetration in electric power systems is increasing rapidly. The risks associated with maintaining the short-term power balance as well as long-term supply continuity can increase significantly with increase in wind power penetration due to the uncertainty in power fluctuations from wind sources. The operation of different types of generating units requires proper coordination to minimize the operating risks and to increase the utilization of wind energy. Such coordination can however significantly affect the long-term system adequacy. This paper presents reliability models in Monte Carlo simulation that incorporate coordination between thermal, hydro and wind energy sources, and can be used to evaluate renewable energy usage and the long-term system reliability. The method is applied to the IEEE Reliability Test System to assess the impact of generating unit coordination on the system adequacy and the amount of wind and hydro energy utilization. The impact of coordination on system reliability and water usage are investigated considering reservoir limitations, varying wind penetration, and wind regimes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".